1. Field of the Invention
The present invention relates to the field of characterizing and modeling the interaction between tissues and organs in an organism, by exchange of neural signals or of chemical or cellular material.
2. Related Art
In both paper and digital forms, there are numerous biomedical “atlases”. A substantial number of these map the human brain. Other atlases map other parts of the body, or part of another species, such as the brain of the rat. Uniformly, these atlases resemble the physical or ecological aspect of a geographical atlas: the pages that subdivide the world into land and sea, high and low, forest and tundra. There are three important types of mapping. Segmentational mapping divides the world into a set of discrete regions, such as political pages in a geographical atlas. Classificatory mapping describes continuous quantities, such as rainfall or height above sea level. Communication mapping describes paths that can be taken for certain journeys.
Early communication maps of the ocean were widely covered with rhumb lines. Rhumb lines are constant-compass-heading paths appropriate for a large set of typical journeys. Rhumb lines became less necessary with the invention of the Mercator projection, which made it possible to take two points, draw a rhumb line with a ruler, and find the corresponding compass heading with a simple protractor reading. Rhumb lines became obsolete with the development of reliable longitude measurements, which let navigators accurately follow the variable heading Great Circle routes. However, trade route maps remain important in planning navigation commerce and managing seaborne empires. In addition, the rise of land transport increased the importance of trade routes in road and rail atlases. In fact, typical U.S. drivers carry an atlas where the state and county boundary lines are less conspicuous than the highways or trade routes.
In an organism, and particularly in the brain of an organism, communication pathways are important. For example, the white matter of the brain is a mass of communicating neural material, analogous to the jumble of wires connecting the digital devices in an office. Specialized bundles of neurons are called nerves. The optic nerve connects an eye to the image processing and analysis services of the visual cortex at the back of the head.
As another example, damage to a brain artery deprives oxygen to the brain cells downstream of the lesion (damage), so that blood flow pathways determine the effects of a stroke. Blood vessels transmit chemical signals, either as part of the general circulation (melatonin passes into the blood as an “all points bulletin” detected throughout the body) or by specialized anatomy, such as the portal veins that specifically connect the lower hypothalamus to the anterior pituitary.
Moreover, the same structure may serve as a pathway for more than one form of communication, at more than one speed. If a bundle of white matter neurons provides a direct nerve-signal connection between two regions of gray matter, the crawl space between them creates a preferred migration route for unattached cancer cells in metastasis, and perhaps in the future for therapeutically inserted cells or microscopic devices.
It is thus of major medical importance to map these communication pathways. Traditional anatomical atlases represent these communication pathways extremely poorly. For example, FIG. 1 displays a typical slice from a standard brain atlas, showing region outlines precisely, and neural connections as dotted planar curves. Humans, and human heads, are quite variously shaped. To apply a generic map to a particular individual requires adjustment. In brain surgery the standard adjustment is the Talairach-Toumoux brain coordinate system. This locates the symmetry plane, selects two points in it that define a horizontal, and scales blocks to give a correspondence by which these points and the side, front, bottom and back of the brain match in the reference brain and the brain of the subject. (For a recent survey of such “warping” transformations, see A. W. Toga & J. C. Mazziotta, Brain Mapping, Vols. 1-3, (2000).) Nerve connections in the Talairach-Toumoux system are shown by sketchy dotted lines projected onto these planar slices. Since it is rare for a nerve connection to actually lie within any flat plane, let alone one chosen for slicing, such projections cannot and do not try to fully specify the shape of the nerve connection. The nerve connections usually take the shortest, straightest route, circumventing objects very closely, but this three-dimensional (3D) circumvention cannot be displayed in the flattened two-dimensional (2D) imaging of the atlas. Thus, the representation of communication pathways by flat planes or 2D imaging is a limitation in the current art.
Another example of current deficiencies in the present art is shown in FIG. 2, which displays a typical published route or “road map” of lymphatic connections in the breast region. (This is available at http://webmd.lycos.com/content/dmk/dmk article 3961314). The use of this “road map” requires the user to have strong 3D understanding to interpret 2D points in the breast that are at risk, since it is not integrated with a computable model of the anatomy. Thus, relying on the user's interpretation of images is a limitation in the current art.
A third example of current deficiencies in the present art is shown in FIG. 3, which displays a 2D density function (as contours and as a graph) analogous to the 3D densities from which it is desirable to extract branching curves representing channels. This mapping process is discussed in John Reintgen et al., Accurate Nodal Staging of Malignant Melanoma 7 (http://www.moffitt.usf.edu/cnaejrnl/v2n5/article4.html). As above, this mapping process relies on the user's interpretation of 2D images. A detectable marker material (such as vital blue dye or technetium-labeled sulfur colloid) is injected at the site of the primary melanoma to determine the nearby lymph nodes at which measurable quantities of the marker appear. The transport processes themselves are neither mapped nor modeled by more than a geometric model. This mapping of a geometric model is not as preferable as a dynamic model or an active model. In our usage, a geometric model specifies positions of points, curves, surfaces and solids, a dynamic model specifies interactions between parts, while an active model embodies these interactions. For example, the geometric model of a car engine specifies the shapes and relative positions of its parts. The dynamic model of a car engine specifies the internal combustion process, the transmission of forces, the control mechanisms, etc. However, it is still mere description (e.g., via the equations that must be solved to determine what happens). The active model contains processes (moving wheels for a mechanical solar system model, sequenced numerical events in a digital model) that correspond to processes in the system it models. In the car engine example, the active model includes an equation solver that, given inclination of the road, pressure on the accelerator, etc., computes combustion rates and forces according to the rules in a dynamic model, and produces specific numbers for the motion of the car. Thus, there is a need for dynamic models, active models built on the dynamic models, and geometric models. There is a further need for an organizational system that groups active models of subsystems into a larger active model.